Private equity fund valuation and due diligence analysis system and method with deal-level benchmark

ABSTRACT

Private equity fund valuation and due diligence analysis software that combines available information on private equity funds, the organizations and individuals managing these funds, the underlying deals for these funds and companies comparable to the deals for these funds and utilizes multivariate statistical regression or other possible analysis techniques to develop highly accurate approximate deal-level performance benchmarks, value driver analyses, fund-level performance forecasts and fund rating scores. These analyses allow investors to assess the attractiveness of an investment into a given private equity fund with a much greater level of detail.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of U.S. Provisional PatentApplication No. 60/586,986, filed on Nov. 2, 2005.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

Not Applicable.

THE NAMES OF THE PARTIES TO A JOINT RESEARCH OR DEVELOPMENT

Not Applicable.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates to financial analysis tools to valueprivate equity fund investments and to assess the quality of privateequity fund managers based on a variety of quantitative analyses andperformance benchmarks. The tool allows investors to assess theattractiveness of an investment into a given private equity fund with amuch greater level of detail based on several analysis includingfollowing. One element of this tool is a system and method to combineavailable information on fund-level performance and the characteristicof underlying deals for these funds that utilizes for examplemultivariate statistical regression or other possible analysistechniques to develop highly accurate approximate deal-level benchmarks.A second element of this tool is a system and method to combineavailable information on the historic cash flow pattern of privateequity funds and the characteristics of these funds at different pointsin time, the underlying deals for these funds and the characteristics ofthe fund managers over time that utilizes multivariate statisticalregression or other possible analysis techniques to forecast expectedfuture returns to these funds at a high level of accuracy. A thirdelement of this tool is a system and method to combine data on thefinancial performance, accounting performance and capital structure of afocal private equity deals with the financial performance, accountingperformance and capital structure of comparable publicly traded orprivately held companies to use mathematical calculations to quantifythe performance impact of different value drivers in the focal privateequity deal and to benchmark these with comparable figures for thecomparable companies.

2. Description of Related Art Including Information Disclosed Under 37CFR 1.97 and 1.98

Investors in the financial community currently assess the pastperformance of private equity fund managers by comparing averagefund-level performance to commercially available average fundperformances. No data on average deal-level performance is currentlycommercially available, as such data is confidential.

The accurate selection of private equity fund managers is as crucial forthe performance of one's private equity portfolio as it is challenging.Data paucity, few benchmarking possibilities and the long time lagbetween commitment decisions and performance outcomes in the past havemade private equity fund due diligence still look more like an art thana science.

U.S. Patent Application #20060143105, published Jun. 29, 2006 by Coates,describes portable alpha-plus financial products having a private equitycomponent. The financial product includes a cash component, an alphaengine component, a private equity component and a beta component. Thecash component includes an investment in a liquid portfolio. The alphaengine component includes an investment in an alpha-generatingportfolio. The private equity component includes an investment in theprivate equity portfolio. The beta component is structured to track atotal return of one or more indices.

U.S. Patent Application #20030028467, published Feb. 6, 2003 by Sanborn,claims a method and system of raising online venture capital in theprivate equity and debt markets, for raising capital for early stage,primarily privately held, companies through a broker-dealer and privatefunds which attempts to maximize the number of investors and a low perunit investment cost to provide wider participation in the privateequity market while promoting diversification of risk. Because of theneed to limit costs associated with managing such small funds,investment criteria would often be tied to due diligence undertaken bythird parties or to pre-set, objective criteria.

U.S. Patent Application #20040148248, published Jul. 29, 2004 by Allen,discloses a facility that provides information about and enablessecondary transfers of restricted interests in issuers. A method isprovided that includes receiving from users, buy or sell orders, each ofthe buy or sell orders being for an amount of an identified restrictedinterest to be subjected to a secondary transfer at a proposed value,and displaying the buy and sell orders for review by online or offlineusers. Implementations of the invention may include one or more of thefollowing features. The restricted interests comprise interests inlimited partnerships. The restricted interests comprise interests inprivate companies. Information is displayed about an issuer of therestricted interest. Permission of the issuer of the restricted interestis obtained to display the information about the issuer. The proposedvalue is expressed relative to an asset value associated with theinterest. The proposed value is expressed as a percentage of the netasset value of the interest. The proposed value takes account ofcharacteristics of the issuer of the interest. The proposed value takesaccount of historic information associated with the issuer or theinterest. The proposed value takes account of market conditions. Theamount of the identified restricted interest represents a fundedcommitment and an unfunded commitment. The online users comprisepotential buyers and sellers of restricted interests. The online userscomprise an issuer of the restricted interest.

U.S. Patent Application #20060100946, published May 11, 2006 byKazarian, indicates a co-investment structure that aligns interestsamong investors and investment managers by creating pure performancebased compensation for the investment manager while overcoming theconundrum facing asset allocators in selecting investment managers. Theco-investment structure provides cash-based evaluation of performanceand offers multi-option hurdle rate alternatives that accommodate theperformance benchmarks of major asset classes while establishing acompensation structure using granular stratification of relativeperformance. The co-investment structure bases investment managercompensation solely on excess profits, actually cultivatingentrepreneurial returns. In particular, the best entrepreneurialinvestment managers, singularly focused on achieving excess profit withrespect to a top quartile benchmark, excel with the co-investmentstructure. A table of exemplary data comparing hurdle rate overhistorical periods is shown. The table includes a comparison of fivecommonly used benchmarks with a hedge fund index over four consecutivetime periods. The table also includes a comparison of five benchmarkswith a private equity index over four consecutive time periods. Thespecific percentages indicate the returns or performance required to bewithin the top quartile. Such data is used by fiduciaries in an effortto properly distribute assets under management.

U.S. Patent Application #20050171883, published Aug. 4, 2005 by Dundas,puts forth a method and system for asset allocation. The method andsystem matches an investor's objectives for portfolio investment returnand risk with an assessment of a range of expected returns and risksthat are likely to be generated by investment portfolios consisting atleast in part of alternative asset classes that involves, for example,selecting available historical data for a plurality of alternative assetclasses, unsmoothing the historical data based at least in part onhistorical data for traditional asset classes related to the respectivealternative asset classes, and correcting the historical data for thealternative asset classes for an impact of survivorship and selectionbiases. A forecast of an expected return and risk is computed for eachof the alternative asset classes, based at least in part on theunsmoothed and corrected historical data for the alternative assetclasses, and at least one of the alternative asset classes that has anexpected return and risk that corresponds substantially to theinvestor's objectives for portfolio investment return and risk isidentified for inclusion in the investment portfolio.

U.S. Patent Application #20040249687, published Dec. 9, 2004 by Lowell,concerns, a system and method of evaluating investment fund managerperformance including collecting career information for a plurality ofinvestment fund managers, collecting fund information for a plurality ofinvestment funds across a fund universe, associating the careerinformation of an investment fund manager to the fund information forrelated investment funds to generate career performance information foreach of the plurality of investment fund managers, determining a groupof investment fund managers based on at least one criterion, comparingthe career performance information of at least one member of the groupto a benchmark to generate at least one career performance record, andanalyzing the at least one career performance record.

U.S. Patent Application #20050187866, published Aug. 25, 2005 by Lee,illustrates a web-based method and system that facilitates businesstransactions, including the raising of capital in global financialmarkets via the Internet. Users of the system design, structure, analyzeand execute business transactions over the Internet. Users of the systemdescribed include issuers, financial institutions, intermediaries, otherprofessional advisors (law firms, accounting firms, translationagencies, etc.) and end investors. A security means controls access tothe system and restricts access to the system to only qualified users.Users of the system design and diagram a transaction structure, assigncorresponding attributes to the structure design. The structure designand corresponding attributes are stored in a database. The transactionis posted as a notice or interest onto the system, wherein a usermaintains the posting. A database of user and transaction information iscompiled and maintained. The user profile is compared with the postedtransactions to identify transactions of interest to a user. Thetransaction information is communicated to the user. The transaction isexecuted, including issuing new securities or buying or sellingpreviously issued securities through an auction or trade process. Thesystem provides users direct access to its community, which includes,but is not limited to, issuers, investors, intermediaries, and advisorssuch as law firms, consultancy firms, accounting firms, and translationagents.

Two U.S. Patent Applications, #20050144135 published Jun. 30, 2005 and#20050131830 published Jun. 16, 2005 by Juarez, claim a private entityprofile network for private equity and debt funding operations, whereinresource providers define electronic data collection templates to befilled in by prospective resource consumers to form semi-homogeneousprofiles. Providers and/or consumers can assign themselves and/or thirdparties various individualized levels of permissions to access and toperform activities on the profiles. Providers can organize profiles intoportfolios to further manage the data. All accesses and activities, suchas changes to the data, are tracked and recorded in logs useful foraudit purposes.

U.S. Patent Application #20060167777, published Jul. 27, 2006 by Shkedy,describes a method and apparatus for determining investment managerskill. The method of evaluating an investment manager's skill includesdetermining a time frame including a plurality of time periods of apredefined duration over which to calculate statistics, generating areturn distribution for each time period, obtaining return data for amanager for each given time period, standardizing the manager's returndata for each given time period, and calculating measurement statisticsto compare the manager's return data against the return distributionover the plurality of time periods.

What is needed is a system and method to combine available informationon private equity funds, the underlying investments of these funds, theorganizations and individuals who manage these funds, publicly traded orprivately held firms with characteristics that are similar to theunderlying investment of these funds into a financial analysis tools tovalue private equity fund investments and to assess the quality ofprivate equity fund managers based on a variety of quantitative analysesand performance benchmarks.

BRIEF SUMMARY OF THE INVENTION

An object of the present invention is to provide a system and method tocombine available information on private equity funds, the underlyinginvestments of these funds, the organizations and individuals who managethese funds, publicly traded or privately held firms withcharacteristics that are similar to the underlying investment of thesefunds into a financial analysis tools to value private equity fundinvestments and to assess the quality of private equity fund managersbased on a variety of quantitative analyses and performance benchmarks.The tool allows investors to assess the attractiveness of an investmentinto a given private equity fund with a much greater level of detail.

In brief, the present invention relates to an analysis system and methodfor a private equity (PE) fund valuation due diligence tool includingdeal-level benchmark, performance forecasting, value decomposition andfund rating functionality.

The overall method comprises the following components: data onfund-level performance (e.g. the underlying cash flows) for PE fundsover time—commercially available from different sources; data ondeal-level PE fund investment characteristics over time (e.g. thetransaction dates, investment stage, size, age, industry of the acquiredcompany etc.)—commercially available from different sources; data on PEfund characteristics (e.g. size, strategic focus etc.)—commerciallyavailable from different sources; data on PE fund managercharacteristics (e.g. team size and composition, capital undermanagement, age etc.)—commercially available from different sources;stock market, company and accounting data of publicly tradedcompanies—commercially available from different source; a statisticalmodel to calculate “deal-level performance coefficients” for theperformance impact of different deal-characteristics; software or methodto calculate deal-level benchmark based on the deal-level performancecoefficients; a statistical model to calculate “historic payoff patterncoefficients” for the impact of historic PE fund characteristics onfuture and final PE fund performance; software or method to forecastapproximate future and final PE fund performance based on the historicpayoff pattern coefficients; a statistical model to calculate “fundrating coefficients” for the impact of prior PE fund and PE fund managercharacteristics measured at the time of fundraising for a focal fund onfuture and final performance of that focal fund; software or method toforecast approximate future and final performance of a focal fund basedon the fund rating coefficients as a fund rating device; software ormethod to measure the selection efficiency of a given method to selectPE funds from a pool of PE funds offered to investors based on ananalysis of the average portfolio performance realized through thismethod with (a) the average performance of all PE funds offered toinvestors and (b) the average ex-post performance of the best x % of thePE funds offered to investors; software or method to decompose equityreturns from public equity or private equity investments into thefollowing four components: revenue growth effect, margin effect,multiple expansion effect, leverage effect; software or method tocompare (benchmark) the equity returns from PE investments to comparableinvestments in publicly traded or privately held in terms of (a) overallequity returns, (b) revenue growth effect, (c) margin effect, (d)multiple expansion effect, (e) leverage effect; a method to ‘browse’conveniently through a large number of due diligence analyses for agiven PE fund that allows (a) changing the unit of analysis (e.g. movingfrom the portfolio-level to the fund-level to the deal-level) withineach type of analysis and (b) switching from one type of analysis toanother type of analysis (e.g. moving from the PE deal-level benchmarkto the value decomposition analysis) within one level of analysis demoof the Private Equity fund valuation and due diligence Tool that it usesHTML programming to allow the users to ‘browse conveniently’ through theanalysis. In doing so, users can chose one type of analysis (Deal-LevelPE Performance Benchmark, PE Fund Performance Forecaster, ValueDecomposition Analysis, Value Decomposition Benchmark or PE Fund RatingAnalysis) and then changing the unit of analysis (e.g. moving from theportfolio-level to the fund-level to the deal-level) within each type ofanalysis. Alternatively they can stay at a given level of analysis (i.e.fund III) and switch one type of analysis to another type of analysis(e.g. moving from the PE deal-level benchmark to the value decompositionanalysis).

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

These and other details of my invention will be described in connectionwith the accompanying drawings, which are furnished only by way ofillustration and not in limitation of the invention, and in whichdrawings:

FIG. 1 is a diagrammatic view of a table showing data on fundperformance;

FIG. 2 is a diagrammatic view of a table showing data on dealcharacteristics of private equity funds;

FIG. 3 is a diagrammatic view of a table showing a combination of inputdata on fund-level performance for private equity funds over time and ondeal-level private equity fund investment characteristics over time;

FIG. 4 is a diagrammatic view of a table showing an output ofstatistical analysis on deal-level performance coefficients;

FIG. 5 is a diagrammatic view of a flow chart of the deal-levelbenchmark methodology of the present invention;

FIG. 6 is a diagrammatic view of a table showing data on fundperformance and characteristics over time;

FIG. 7 is a diagrammatic view of a table showing a combination of inputdata on fund-level performance for private equity funds over time, ondeal-level private equity fund investment characteristics over time, andon private equity fund characteristics;

FIG. 8 is a diagrammatic view of a table showing an output ofstatistical analysis as historic payoff pattern coefficients;

FIG. 9 is a diagrammatic view of a flowchart showing the methodology fora private equity fund performance forecaster;

FIG. 10 is a diagrammatic view of a table showing data on historicalfundraising situations;

FIG. 11 is a diagrammatic view of a timeline using data from pastfundraising situations;

FIG. 12 is a diagrammatic view of a table showing an output ofstatistical analysis as fund rating coefficients;

FIG. 13 is a diagrammatic view of a flowchart showing the methodologyfor private equity fund rating;

FIG. 14 is a diagrammatic view of a graph showing fund selection IRRcomparison.

DETAILED DESCRIPTION OF THE INVENTION

The present invention comprises a system method employing a softwareprogram as a private equity (PE) fund valuation and due diligence toolincluding deal-level benchmark, performance forecasting, valuedecomposition and fund rating functionality. The tool allows investorsto assess the attractiveness of an investment into a given privateequity fund with a much greater level of detail.

A private equity fund valuation and due diligence system includingdeal-level benchmark, performance forecasting, value decomposition andfund rating functionality, the system comprising a software programproviding a valuation and due diligence analysis tool using hyper textmarkup language programming to allow a user to browse through ananalysis choosing one type of analysis taken from the list of types ofanalysis including deal-level private equity performance benchmarkanalysis, private equity fund performance forecaster analysis, valuedecomposition analysis, value decomposition benchmark analysis, andprivate equity fund rating analysis and to change the unit of analysisswitching from one level of analysis to another between the levels ofanalysis including the portfolio-level analysis, the fund-levelanalysis, and the deal-level analysis within each type of analysis andalternatively to stay at one level of analysis and switch one type ofanalysis to another type of analysis.

In detail, the private equity fund valuation and due diligence systemincluding deal-level benchmark, performance forecasting, valuedecomposition and fund rating functionality, the system comprises:

a software program with a series of data gathering and analysis programsfor use as a private equity (PE) fund valuation and due diligence toolincluding deal-level benchmark, performance forecasting, valuedecomposition and fund rating functionality, the system comprising thefollowing components:

(1) data on fund-level performance for private equity funds over time;

(2) data on deal-level private equity fund investment characteristicsover time;

(3) data on private equity fund characteristics;

(4) data on private equity fund manager characteristics;

(5) stock market, company and accounting data of comparable publiclytraded or privately held companies;

(6) a statistical model for calculating deal-level performancecoefficients for the performance impact of differentdeal-characteristics;

(7) a program for calculating a deal-level benchmark based on deal-levelperformance coefficients;

(8) a statistical model for calculating historic payoff patterncoefficients for the impact of historic private equity fundcharacteristics on future and final private fund performance;

(9) a program for forecasting approximate future and final privateequity fund performance based on the historic payoff patterncoefficients;

(10) a statistical model for calculating fund rating coefficients forthe impact of prior private equity fund and private equity fund managercharacteristics measured at the time of fundraising for a focal fund onfuture and final performance of that focal fund;

(11) a program for forecasting approximate future and final performanceof a focal fund based on the fund rating coefficients as a fund ratingdevice;

(12) a program for measuring the selection efficiency of a given methodto select private equity funds from a pool of private equity fundsoffered to investors based on an analysis of the average portfolioperformance realized with (a) the average performance of all PE fundsoffered to investors and (b) the average ex-post performance of the bestpercentage of the PE funds offered to investors;

(13) a program for decomposing equity returns from public equity orprivate equity investments into the following four components: revenuegrowth effect, margin effect, multiple expansion effect, and leverageeffect;

(14) a program for performing benchmark comparisons of the equityreturns from private equity investments to comparable public equityinvestments in terms of (a) overall equity returns, (b) revenue growtheffect, (c) margin effect, (d) multiple expansion effect, and (e)leverage effect to provide deal-level benchmarks; and

(15) a program for browsing through a large number of due diligenceanalyses for a given private equity fund, the program for browsingallowing changing the unit of analysis within each type of analysis andswitching from one type of analysis to another type of analysis withinone level of analysis.

Based on these components, the following analyses, described below inmore detail, will be performed: Deal-Level PE Performance Benchmark, PEFund Performance Forecaster, Value Decomposition Analysis, ValueDecomposition Benchmark, PE Fund Rating Analysis.

For the Deal-Level PE Performance Benchmark, the “deal-level performancecoefficients” (6) that measure the performance impact of differentdeal-characteristics on PE Fund performance, in FIG. 4, are calculatedbased on the data from paragraphs (1) and (2) above, in FIGS. 1 and 2and combined in FIG. 3, using standard statistical software package(e.g. SPSS or Stata); then these deal-level performance coefficients areused to calculate the deal-level PE performance benchmark, using eithera simple Excel sheet or a specific software program of paragraph (7)above according to the flowchart of FIG. 5. Based on these coefficients,the deal-level benchmarks can be calculated (7): e.g. approximatedaverage Performance of 1990 Biotech deal=14%+8%+3%=25% IRR.

One could use the same main idea: combining fund-level performance anddeal-level investment characteristics to approximate deal-levelperformance using different statistical techniques.

For the PE Fund Performance Forecaster, the “historic payoff patterncoefficients” that measure the impact of historic PE fundcharacteristics on future and final PE fund performance are calculatedbased on the data from paragraphs (1), (2) and (3) above, as showncombined in FIG. 7, by combining the data of paragraph (1) and (3), asshown in FIG. 6 with the data of paragraph (2), as shown in FIG. 2,using standard statistical software package (e.g. SPSS or Stata); thenthese historic payoff pattern coefficients are used to forecast theperformance of PE funds with given characteristics using either a simpleExcel sheet or a specific software program of paragraph (9) above, asshown in FIG. 8 according to the method of the flowchart of FIG. 9.

Based on these coefficients, the performance forecast for a fund of agiven age and with given investment characteristics can be calculated(9):

e.g. Forecasted Performance of a two-year old fund with unrealized dealsworth 20% of called capital on the books, 50% of committed capitalcalled and a performance of 10%is:=2%+20%*5%+50%*3%+1,2*10%=2+1+1,5+12%=14,5% IRR

One could use the same main idea: combining historic fund-levelcharacteristics and final performance of a pool of PE funds to forecastPE fund performance using different statistical techniques.

For the Value Decomposition Analysis, the change equity value of abusiness can be broken down into the following four determinants (13):revenues, margin, valuation multiple and net debt. The followingformulae are based in part on an article co-authored by the presentinventor (“Working out where the value lies”, European Venture CapitalJournal, June 2004 (O. Gottschalg, N. Loos, M. Zollo)) although thepresent invention goes beyond the article in integrating the formulae asa small part of the system and method of the present invention withapplications and many elements not found in the article. Usingcompounded annual growth rates (CAGRs) of all four components, the IRR(as the CAGR of the equity value) can be expressed as:

(1+(CAGR(E))=(1+(CAGR(Re)))(1+(CAGR(EBITDA/Rev)))(1+CAG((EV/EBITDA)))(I+(CAGR(E/EV)))

with (1+CAGR(E)) being equivalent to 1+IRR(Equity). To understand whatportion of the overall IRR is determined by each of these components,calculate:

100% = (ln (1 + (CAGR(Rev)))/ln (1 + CAGR(E))) + (ln (1 + CAGR(EBITDA/Rev)))/ln (1 + (CAGR(E))) + (ln (1 + (CAGR((EV/EBITDA)))/ln (1 + CAGR(E))) + ln (1 + (CAGR(E/EV))/ln (1 + (CAGR(E)))

with (1+CAGR(E)) being equivalent to 1+IRR(Equity). To understand whatportion of the overall IRR is determined by each of these components, wecan calculate:

IRR(Equity) = IRR(Equity)(ln (I + (CAGR(Rev)))/ln (1 + (CAGR(E))) + IRR(Equity)(ln (1 + (CAGR(EBITDA/Rev)))/ln (1 + (CAGR(E))) + IRR(Equity)(ln (1 + CAGR((EV/EBITDA)))/ln (1 + (CAGR(E))) + IRR  (Equity)(ln (1 + (CAGR(E/EV)))/ln (1 + (CAGR(E)))

These values can be interpreted in the following way:

IRR(Equity) = Revenue  growth  effect  (on  IRR) + EBITDA  margin  effect  (on  IRR) + Multiple  expansion  effect  (on  IRR) + Leverage  Effect  (on  IRR).

Each bracket now represents the relative contribution of revenuesgrowth, margin improvement, multiple expansion and leverage to IRR,adding up to 100%. By multiplying both sides with the equity IRR, wefind each factor's absolute contribution to the level of IRR, hence

These values can be interpreted in the following way:

IRR(Equity) = Revenue  growth  effect  (on  IRR) + EBITDA  margin  effect  (on  IRR) + Multiple  expansion  effect  (on  IRR) + Leverage  Effect  (on  IRR).

For the Value Decomposition Benchmark, the Value Decomposition Analysisas described above is performed for one (or multiple) PE investment andone or a sample of comparable publicly traded (‘peer’) companies (usingdata from (5)). The comparison in each of the four value drivers(Revenue growth effect, Margin effect, Multiple expansion effect,Leverage Effect.) between these two for a given time period makes itpossible to determine to what extent element of the value change of thePE investment is related to changes in the corresponding value driver ofthe publicly traded peer(s) (14).

Provided data is available, a comparison with one or multiple comparablePE investments in each value driver is equally possible.

The Private Equity fund valuation and due diligence Tool of the presentinvention provides its user with many charts and analyses.

For the PE Fund Rating Analysis, several of the previous analyses arecombined and, together with other ratios, used to derive a rating schemefor PE funds. Looking at historic data on PE funds managed by a given PEfund manager, as in paragraphs (1), (2), (3) and (4) above, as of themoment in time when a new (focal) fund was raised by this fund manager,as seen in FIGS. 10 and 11, the present invention statistically links anumber of measures of PE fund and PE fund manager characteristics,including past performance (including measures based on the Deal-LevelPE Performance Benchmark, the PE Fund Performance Forecaster, the ValueDecomposition Analysis and the Value Decomposition Benchmark), strategy,team resources and experience, to the later performance of these focalfunds. This can be done, for example, through a multivariate regressionor other possible analysis of the PE fund and PE fund managercharacteristics measured at the time a focal fund is raised on the laterperformance of these focal funds that estimates the ‘fund ratingcoefficients’ of paragraph (10) above, as shown in FIG. 12; then thesefund rating coefficients are used to estimate the expected performanceof a focal PE fund with given Fund and fund manager characteristics atfundraising using either a simple Excel sheet or a specific softwareprogram of paragraph (11) above as illustrated in the flowchart of FIG.13.

Based on these coefficients, the fund rating for a to-be-raised fundwith given characteristics can be calculated (11):

e.g. Fund Rating of a 20 Mio $ fund with an IRR of the prior fund of15%, a change in size of 150% and 1 prior funds comes tois:=6%+20*0,002+15%*1,2+150%*(−0,023)+1*0,2=6%+4%+18%-3,45%+20%=44,55%.

In FIG. 14, the efficiency of a given method (for example based on aparticular version of the PE Fund Rating Analysis) to select PE fundsfrom a pool of PE funds offered to investors (13) is measured as theratio of (a) and integral of the difference between the averageperformance of all PE funds offered to investors and the averageperformance of the best x % of the PE funds as predicted by theselection method (b) integral of the difference between the averageperformance of all PE funds offered to investors and the averageperformance of the actual best x % (ex-post) of the PE funds offered toinvestors.

In case of a typical Fund Due Diligence process, in which severalprevious funds, each with between 10 and 100 investments are beinganalyzed, the number of charts can be several hundred. To guide the usethrough this ‘jungle’ of information, a particular logic has beendeveloped. It uses HTML programming to allow the users to ‘browseconveniently’ through the analysis (15). In doing so, they can chose onetype of analysis (Deal-Level PE Performance Benchmark, PE FundPerformance Forecaster, Value Decomposition Analysis, ValueDecomposition Benchmark or PE Fund Rating Analysis) and then changingthe unit of analysis (e.g. moving from the portfolio-level to thefund-level to the deal-level) within each type of analysis.Alternatively they can stay at a given level of analysis (i.e. fund III)and switch one type of analysis to another type of analysis (e.g. movingfrom the PE deal-level benchmark to the value decomposition analysis).

Example of Use of the Private Equity Fund Valuation and Due DiligenceTool: Currently potential investors into PE funds typically analyze thefund proposed to them based on a limited number of analyses that haveseveral shortcomings. (a) They mostly focus on aggregate fund-levelperformance only: imagine a given fund that made 20 investments with anaverage yearly performance of 20%, then this will be compared to theaverage fund-level performance of all funds raised in the same year(e.g. 15%) to conclude that this is a good fund. (b) More detailedanalyses of individual deals and value drivers often occur manually, adhoc and with little possibility to benchmark the reported performancefigures (it is private equity and little to no disclosure requirementsexist). The Private Equity Fund Valuation and Due Diligence Tool enablesthem to use all the information on the performance and characteristicsof the 20 individual investments in the sample and compare them indetail to average (public or private equity) investments that happenedin the same industry, are of comparable size and/or happened during thesame year etc. My technique furthermore quantifies the characteristicsof a proposed fund in a fund rating scheme that makes it possible toeasily compare the attractiveness of different funds and to assess theselection efficiency to alternative fund selection rules.

In use, a private equity fund valuation and due diligence methodincluding deal-level benchmark, performance forecasting, valuedecomposition and fund rating functionality, comprises using a softwareprogram to serve as a due diligence tool using hyper text markuplanguage programming to allow a user to browse through an analysischoosing one type of analysis taken from the list of types of analysisincluding deal-level private equity performance benchmark analysis,private equity fund performance forecaster analysis, value decompositionanalysis, value decomposition benchmark analysis, and private equityfund rating analysis and to change the unit of analysis switching fromone level of analysis to another between the levels of analysisincluding the portfolio-level analysis, the fund-level analysis, and thedeal-level analysis within each type of analysis and alternatively tostay at one level of analysis and switch one type of analysis to anothertype of analysis.

In detail the private equity fund valuation and due diligence methodincluding deal-level benchmark functionality comprises the followingsteps:

A first step of gathering data on fund-level performance for privateequity funds over time, the step comprising gathering data on theprivate equity fund cash flows.

A second step of gathering data on deal-level private equity fundinvestment characteristics over time, the step comprising gathering dataon the investment characteristics of transaction dates, stage, age,size, country and industry sector.

A third step of gathering data on private equity fund characteristics,the step comprising gathering data on the equity fund characteristics ofregion, vintage year, size and investment focus.

A fourth step of gathering data on private equity fund managercharacteristics, the step comprising gathering data on the equity fundmanager characteristics of team size, team composition, biographicaldata of investment managers, capital under management, and age.

A fifth step of gathering stock market, company and accounting data ofpublicly traded companies.

A sixth step of using a statistical model to calculate deal-levelperformance coefficients for the performance impact of differentdeal-characteristics.

A seventh step of calculating a deal-level benchmark based on deal-levelperformance coefficients, the step comprising using a software programto calculate a deal-level benchmark.

An eighth step of using a statistical model to calculate historic payoffpattern coefficients for the impact of historic private equity fundcharacteristics on future and final private fund performance.

A ninth step of forecast approximate future and final private equityfund performance based on the historic payoff pattern coefficients, thestep comprising using a software program to calculate a deal-levelbenchmark based on deal-level performance coefficients, the stepcomprising using a software program to forecast approximate future andfinal private equity fund performance.

A tenth step of using a statistical model to calculate fund ratingcoefficients for the impact of prior private equity fund and privateequity fund manager characteristics measured at the time of fundraisingfor a focal fund on future and final performance of that focal fund.

An eleventh step of forecasting approximate future and final performanceof a focal fund based on the fund rating coefficients as a fund ratingdevice, the eleventh step comprising using a software program toforecast approximate future and final performance of a focal fund.

A twelfth step of measuring the selection efficiency of a given methodto select private equity funds from a pool of private equity fundsoffered to investors based on an analysis of the average portfolioperformance realized through this method with (a) the averageperformance of all PE funds offered to investors and (b) the averageex-post performance of the best percentage of the PE funds offered toinvestors, the step comprising using software to measure the selectionefficiency.

A thirteenth step of decomposing equity returns from public equity orprivate equity investments into the following four components: revenuegrowth effect, margin effect, multiple expansion effect, and leverageeffect, the step comprising using a software program to decompose equityreturns.

A fourteenth step of performing benchmark comparisons of the equityreturns from private equity investments to comparable public equityinvestments in terms of (a) overall equity returns, (b) revenue growtheffect, (c) margin effect, (d) multiple expansion effect, and (e)leverage effect, the step comprising using a software program to comparethe equity returns from private equity investments to comparable publicequity investments.

A fifteenth step of using a method of browsing through a large number ofdue diligence analyses for a given private equity fund, the method ofbrowsing allowing changing the unit of analysis within each type ofanalysis and switching from one type of analysis to another type ofanalysis within one level of analysis, wherein changing the unit ofanalysis comprises moving from the portfolio-level to the fund-level tothe deal-level within each type of analysis, and wherein switching fromone type of analysis to another type of analysis comprises moving from aprivate equity deal-level benchmark to a value decomposition analysiswithin one level of analysis.

The method comprises using a software program to run statistical modelsusing non-linear multivariate regression or other possible analysis tocalculate various performance measures and benchmarks for proposedprivate equity fund investments.

The method comprises using a software program which uses variouscommercially available data sources on performance of private equityfunds, stock market, business and accounting data on publicly tradedfirms and on the characteristics of the investments private equity fundshave made and on the fund managers responsible for the investments. Themethod further comprises using a software program to measure historiccash flows of private equity funds and using a software program toanalyze the characteristics of industry sector, industry size, and timeof the investments private equity funds have made and the fund managersresponsible for the investments.

It is understood that the preceding description is given merely by wayof illustration and not in limitation of the invention and that variousmodifications may be made thereto without departing from the spirit ofthe invention as claimed.

1. A private equity fund valuation and due diligence analysis methodincluding deal-level benchmark, performance forecasting, valuedecomposition and fund rating functionality, the method comprising usinga software program to serve as a valuation and due diligence tool usinghyper text markup language programming to allow a user to browse throughan analysis choosing one type of analysis taken from the list of typesof analysis including deal-level private equity performance benchmarkanalysis, private equity fund performance forecaster analysis, valuedecomposition analysis, value decomposition benchmark analysis, andprivate equity fund rating analysis and to change the unit of analysisswitching from one level of analysis to another between the levels ofanalysis including the portfolio-level analysis, the fund-levelanalysis, and the deal-level analysis within each type of analysis andalternatively to stay at one level of analysis and switch one type ofanalysis to another type of analysis to provide a private equity fundvaluation and due diligence analysis method including deal-levelbenchmark, performance forecasting, value decomposition and fund ratingfunctionality.
 2. A private equity fund valuation and due diligenceanalysis method including deal-level benchmark, performance forecasting,value decomposition and fund rating functionality, the methodcomprising: a first step of gathering data on fund-level performance forprivate equity funds over time; a second step of gathering data ondeal-level private equity fund investment characteristics over time; athird step of gathering data on private equity fund characteristics; afourth step of gathering data on private equity fund managercharacteristics; a fifth step of gathering stock market, company andaccounting data of publicly traded companies; a sixth step of using astatistical model to calculate deal-level performance coefficients forthe performance impact of different deal-characteristics; a seventh stepof calculating a deal-level benchmark based on deal-level performancecoefficients; an eighth step of using a statistical model to calculatehistoric payoff pattern coefficients for the impact of historic privateequity fund characteristics on future and final private fundperformance; a ninth step of forecast approximate future and finalprivate equity fund performance based on the historic payoff patterncoefficients; a tenth step of using a statistical model to calculatefund rating coefficients for the impact of prior private equity fund andprivate equity fund manager characteristics measured at the time offundraising for a focal fund on future and final performance of thatfocal fund; an eleventh step of forecasting approximate future and finalperformance of a focal fund based on the fund rating coefficients as afund rating device; a twelfth step of measuring the selection efficiencyof a given method to select private equity funds from a pool of privateequity funds offered to investors based on an analysis of the averageportfolio performance realized through this method with (a) the averageperformance of all PE funds offered to investors and (b) the averageex-post performance of the best percentage of the PE funds offered toinvestors; a thirteenth step of decomposing equity returns from publicequity or private equity investments into the following four components:revenue growth effect, margin effect, multiple expansion effect, andleverage effect; a fourteenth step of performing benchmark comparisonsof the equity returns from private equity investments to comparablepublic equity investments in terms of (a) overall equity returns, (b)revenue growth effect, (c) margin effect, (d) multiple expansion effect,and (e) leverage effect to provide deal-level benchmarks; and afifteenth step of using a method of browsing through a large number ofdue diligence analyses for a given private equity fund, the method ofbrowsing allowing changing the unit of analysis within each type ofanalysis and switching from one type of analysis to another type ofanalysis within one level of analysis; all combined to provide a privateequity fund valuation and due diligence analysis method includingdeal-level benchmark, performance forecasting, value decomposition andfund rating functionality.
 3. The method of claim 2 wherein step threecomprises gathering data on the equity fund characteristics of size andstrategic focus.
 4. The method of claim 2 wherein the fourth stepcomprises gathering data on the equity fund manager characteristics ofteam size, team composition, capital under management, and age.
 5. Themethod of claim 2 wherein the seventh step comprises using a softwareprogram to calculate a deal-level benchmark based on deal-levelperformance coefficients.
 6. The method of claim 2 wherein the ninthstep comprises using a software program to forecast approximate futureand final private equity fund performance based on the historic payoffpattern coefficients.
 7. The method of claim 2 wherein the eleventh stepcomprises using a software program to forecast approximate future andfinal performance of a focal fund based on the fund rating coefficientsas a fund rating device.
 8. The method of claim 2 wherein the twelfthstep comprises using software to measure the selection efficiency. 9.The method of claim 2 wherein the thirteenth step comprises using asoftware program to decompose equity returns.
 10. The method of claim 2wherein the fourteenth step comprises using a software program tocompare (benchmark) the equity returns from private equity investmentsto comparable public equity investments.
 11. The method of claim 2wherein changing the unit of analysis in the fifteenth step comprisesmoving from the portfolio-level to the fund-level to the deal-levelwithin each type of analysis.
 12. The method of claim 2 whereinswitching from one type of analysis to another type of analysiscomprises moving from a private equity deal-level benchmark to a valuedecomposition analysis within one level of analysis.
 13. The method ofclaim 2 wherein the method comprises using a software program to runstatistical models using analysis techniques to calculate variousperformance measures and benchmarks for proposed private equity fundinvestments.
 14. The method of claim 2 wherein the method comprisesusing a software program which uses various commercially available datasources on performance of private equity funds, stock market, businessand accounting data on publicly traded firms and on the characteristicsof the investments private equity funds have made and on the fundmanagers responsible for the investments.
 15. The method of claim 14wherein the method comprises using a software program to measurehistoric cash flows of private equity funds.
 16. The method of claim 14wherein the method comprises using a software program to analyze thecharacteristics of industry sector, industry size, and time of theinvestments private equity funds have made and the fund managersresponsible for the investments.
 17. A private equity fund valuation anddue diligence system including deal-level benchmark, performanceforecasting, value decomposition and fund rating functionality, thesystem comprising a software program providing a due diligence analysistool using hyper text markup language programming to allow a user tobrowse through an analysis choosing one type of analysis taken from thelist of types of analysis including deal-level private equityperformance benchmark analysis, private equity fund performanceforecaster analysis, value decomposition analysis, value decompositionbenchmark analysis, and private equity fund rating analysis and tochange the unit of analysis switching from one level of analysis toanother between the levels of analysis including the portfolio-levelanalysis, the fund-level analysis, and the deal-level analysis withineach type of analysis and alternatively to stay at one level of analysisand switch one type of analysis to another type of analysis to provide aprivate equity fund valuation and due diligence system includingdeal-level benchmark, performance forecasting, value decomposition andfund rating functionality.
 18. A private equity fund valuation and duediligence system including deal-level benchmark, performanceforecasting, value decomposition and fund rating functionality, thesystem comprising: a software program with a series of data gatheringand analysis programs for use as a private equity (PE) fund valuationand due diligence tool including deal-level benchmark, performanceforecasting, value decomposition and fund rating functionality, thesystem comprising the following components: a program for gathering dataon fund-level performance for private equity funds over time; a programfor gathering data on deal-level private equity fund investmentcharacteristics over time; a program for gathering data on privateequity fund characteristics; a program for gathering data on privateequity fund manager characteristics; a program for gathering stockmarket, company and accounting data of publicly traded companies; astatistical model for calculating deal-level performance coefficientsfor the performance impact of different deal-characteristics; a programfor calculating a deal-level benchmark based on deal-level performancecoefficients; a statistical model for calculating historic payoffpattern coefficients for the impact of historic private equity fundcharacteristics on future and final private fund performance; a programfor forecasting approximate future and final private equity fundperformance based on the historic payoff pattern coefficients; astatistical model for calculating fund rating coefficients for theimpact of prior private equity fund and private equity fund managercharacteristics measured at the time of fundraising for a focal fund onfuture and final performance of that focal fund; a program forforecasting approximate future and final performance of a focal fundbased on the fund rating coefficients as a fund rating device; a programfor measuring the selection efficiency of a given method to selectprivate equity funds from a pool of private equity funds offered toinvestors based on an analysis of the average portfolio performancerealized with (a) the average performance of all PE funds offered toinvestors and (b) the average ex-post performance of the best percentageof the PE funds offered to investors; a program for decomposing equityreturns from public equity or private equity investments into thefollowing four components: revenue growth effect, margin effect,multiple expansion effect, and leverage effect; a program for performingbenchmark comparisons of the equity returns from private equityinvestments to comparable public equity investments in terms of (a)overall equity returns, (b) revenue growth effect, (c) margin effect,(d) multiple expansion effect, and (e) leverage effect to providedeal-level benchmarks; and a program for browsing through a large numberof due diligence analyses for a given private equity find, the programfor browsing allowing changing the unit of analysis within each type ofanalysis and switching from one type of analysis to another type ofanalysis within one level of analysis; all combined to provide a privateequity fund valuation and due diligence system including deal-levelbenchmark, performance forecasting, value decomposition and fund ratingfunctionality.